Merge Desjardins and Ashton trees

Author

Claudia Zirión-Martínez

Published

February 10, 2025

Setup

Code
library(RRphylo)
library(manipulate)
library(ape)
library(phytools)
library(ggtree)
library(tidyverse)
library(RColorBrewer)
library(ggnewscale)
library(patchwork)
source("scripts/metadata_colors.R")

Input and output paths

Code
metadata_ashton_desj_all_weavepop_H99 <- "data/processed/metadata_ashton_desj_all_weavepop_H99.csv"

desj_tree_path <- "data/raw/CryptoDiversity_Desjardins_Tree.tre"
desj_tree_out_path <- "data/processed/tree_desjardins.newick"
desj_tree_out_plot <- "results/trees/tree_desjardins.png"

ashton_tree_path <- "data/raw/2017.06.09.all_ours_and_desj.snp_sites.mod.fa.cln.tree"
ashton_metadata_path <- "../Crypto_Ashton/config/metadata_all_ashton_and_vni_desj.csv"
ashton_tree_out_path <- "data/processed/tree_ashton.newick"
ashton_tree_unrooted_plot <- "results/trees/tree_ashton_unrooted.png"
ashton_tree_rooted_plot <- "results/trees/tree_ashton.png"
ashton_tree_rooted_plot_pdf <- "results/trees/tree_ashton.pdf"

merged_tree_out_path <- "data/processed/tree_merged.newick"
merged_tree_branchlengths_plot <- "results/trees/tree_merged_branchlengths.png"
merged_tree_plot <- "results/trees/tree_merged.png"
merged_tree_small_plot <- "results/trees/tree_merged_small.png"

Metadata

Use the metadata table that has all the samples included in the final Crypto_Desjardins_Ashton dataset and H99 (n = 1056).

Code
metadata <- read.delim(
    metadata_ashton_desj_all_weavepop_H99,
    header=TRUE,
    sep=",")
summary <- metadata %>% 
    group_by(dataset, lineage) %>% 
    summarize(count = n())
summary
dataset lineage count
Ashton VNI 668
Desjardins VNBI 122
Desjardins VNBII 64
Desjardins VNI 185
Desjardins VNII 16
Reference VNI 1

Make separate dataframes for each metadata field.

Code
metadata$vni_subdivision <- factor(metadata$vni_subdivision,
                            levels = names(sublineage_colors))
metadata$country_of_origin <- factor(metadata$country_of_origin,
                                levels = names(country_colors))

sublineage <- metadata %>%
                filter(lineage == "VNI")%>%
                select(strain, vni_subdivision)%>%
                column_to_rownames("strain")%>%
                droplevels()
lineage <- metadata %>%
            select(strain, lineage)%>%
            column_to_rownames("strain")
dataset <- metadata %>%
            select(strain, dataset)%>%
            column_to_rownames("strain")
source <- metadata %>%
            select(strain, source)%>%
            column_to_rownames("strain")
country <- metadata %>%
            select(strain, country_of_origin)%>%
            column_to_rownames("strain")

Desjardins tree

Import the raw Desjardins tree

Code
desj_tree <- read.tree(desj_tree_path)

Reroot the tree at the middle of the branch leading to VNII

Code
VNII_root <- getMRCA(desj_tree, c("C2","C12"))
edge_length <- subset(desj_tree$edge.length, desj_tree$edge[,2] == VNII_root)
desj_tree <- reroot(desj_tree, VNII_root, edge_length/2)
write.tree(desj_tree, file = desj_tree_out_path)
Code
country_desj <- levels(droplevels(country[rownames(country) %in% desj_tree$tip.label, ]))

Ashton tree

Import the raw Ashton tree

Code
ashton_tree_unrooted <- read.tree(ashton_tree_path)

Rename tips to use strain names in the Desjardins samples (which have run accessions).

Code
ashton_tree_unrooted$tip.label <- sapply(ashton_tree_unrooted$tip.label, function(x) {
    if (x %in% metadata$run) {
        metadata$strain[metadata$run == x]
    } else {
        x
    }
})

Get the samples that are present in the tree but absent from the metadata of the final dataset

Code
tips_missing_from_final_dataset <- setdiff(ashton_tree_unrooted$tip.label, metadata$strain)

Compare the list of strains missing from metadata with the oringinal Ashton metadata

Code
ashton_metadata <-read.delim(
    ashton_metadata_path,
    header=TRUE, sep=",")
samples_missing_from_dataset <- ashton_metadata %>%
    filter(strain %in% tips_missing_from_final_dataset)%>%
    select(sample, strain, lineage, VNI_subdivision)
samples_missing_from_dataset
sample strain lineage VNI_subdivision
ERS542414 15277_3#7 VNI VNIa-4
ERS542415 15277_3#8 VNI VNIa-4
ERS542595 15277_3#45 VNI VNIa-4
ERS542403 15277_3#1 VNI VNIa-4
ERS542456 15277_3#18 VNI VNIa-4
ERS542410 15277_3#5 VNI VNIa-5
ERS542411 15277_3#6 VNI VNIa-5
CNS_1465 VNI VNIa-93
ERS542584 15277_3#42 VNI VNIa-93
ERS542502 14893_1#16 VNI VNIa-93

The CNS_1465 strain was not available for download and the rest had bad quality alignments.

Root Ashton tree at the middle of the branch leading to VNIa

Code
VNIa_root <- getMRCA(ashton_tree_unrooted, c("AD3-95a","Tu259-1"))
edge_length <- subset(ashton_tree_unrooted$edge.length, 
    ashton_tree_unrooted$edge[,2] == VNIa_root)
ashton_tree <- reroot(ashton_tree_unrooted, VNIa_root, edge_length/2)
write.tree(ashton_tree, file = ashton_tree_out_path)

Merge Desjardins and Ashton trees

Specify clades in Desjardins tree

Code
VNI <- c("Bt92", "Bt79")
VNI_node <- getMRCA(desj_tree, VNI)
VNII <- c("C2","C12")
VNII_node <- getMRCA(desj_tree, VNII)
VNB <- c("Bt7", "Bt34")
VNB_node <- getMRCA(desj_tree, VNB)

Get the ages of the nodes from the original Desjardins tree. This is to attempt to have a calibrated tree, but the resulting branchlengths are not real.

Code
edge_lengths <- node.depth.edgelength(desj_tree)
node_labels <- c(desj_tree$tip.label, desj_tree$node.label)
edge_length_mapping <- data.frame(
    node = node_labels, 
    edge_length = edge_lengths, 
    max_length = max(edge_lengths))
edge_length_mapping <- edge_length_mapping %>% 
                        mutate(age = max_length - edge_length) %>%
                        rownames_to_column("node_id")
clade_ages <- edge_length_mapping %>% 
                filter(node_id %in% c(VNI_node, VNII_node, VNB_node))
nodeages <- c("Bt92-Bt79" = clade_ages$age[clade_ages$node_id == VNI_node],
             "C2-C12" = clade_ages$age[clade_ages$node_id == VNII_node],
             "Bt7-Bt34" = clade_ages$age[clade_ages$node_id == VNB_node])
tip_ages <- edge_length_mapping %>% 
                filter(node %in% metadata$strain)
tipages <- tip_ages$age
names(tipages) <- tip_ages$node

Remove VNI clade from Desjardins tree to use it as backtree

Code
VNI_tips <- tips(desj_tree, VNI_node)
backtree <- drop.tip(desj_tree, VNI_tips)

Create the reference tables

Code
reference <- data.frame(bind=c("CNS_289-20427_2#4"),
                   reference=c("Bt7-Bt34"),
                   poly=c(FALSE))

Merge

Code
merged <- tree.merger(backbone = backtree,
                        data=reference,
                        source.tree = ashton_tree,
                        plot=FALSE,
                        node.ages = nodeages,
                        tip.ages = tipages)

Plot minimal version of the tree

Get one sample of each non-VNI lineage, VNI sublineage, and all VNIa-outlier

Code
VNI <- metadata %>%
    filter(lineage == "VNI", vni_subdivision != "VNIa-outlier") %>%
    group_by(vni_subdivision) %>%
    slice(1) %>%
    ungroup()
VNIa_outlier <- metadata %>%
    filter(vni_subdivision == "VNIa-outlier")
VNII <- metadata %>%
    filter(lineage == "VNII") %>%
    slice(1) %>%
    ungroup()
VNBI <- metadata %>%
    filter(lineage == "VNBI") %>%
    slice(1) %>%
    ungroup()
VNBII <- metadata %>%
    filter(lineage == "VNBII") %>%
    slice(1) %>%
    ungroup()
tips <- rbind(VNI, VNIa_outlier, VNII, VNBI, VNBII)%>%
    select(strain)

Make a small version of the merged tree only with the tips in tips

Code
small_tree <- drop.tip(merged, setdiff(merged$tip.label, tips$strain))